Abstract
We employ classical statistical methods of multivariate classification for the exploitation of the stellar content of the Hamburg/ESO objective prism survey (HES). In a simulation study we investigate the precision of a three-dimensional classification (Te ,l ogg ,( Fe/H)) achievable in the HES for stars in the eective temperature range 5200 K 10 (typically corresponding to BJ < 16:5). The accuracies in logg and (Fe/H) are better than 0:68 dex in the same S=N range. These precisions allow for a very ecient selection of metal-poor stars in the HES. We present a minimum cost rule for compilation of complete samples of objects of a given class, and a rejection rule for identification of corrupted or peculiar spectra. The algorithms we present are being used for the identification of other interesting objects in the HES data base as well, and they are applicable to other existing and future large data sets, such as those to be compiled by the DIVA and GAIA missions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
